Share Email Print

Proceedings Paper

Programmable genetic algorithm IP core for sensing and surveillance applications
Author(s): Srinivas Katkoori; Pradeep Fernando; Hariharan Sankaran; Adrian Stoica; Didier Keymeulen; Ricardo Zebulum
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Real-time evolvable systems are possible with a hardware implementation of Genetic Algorithms (GA). We report the design of an IP core that implements a general purpose GA engine which has been successfully synthesized and verified on a Xilinx Virtex II Pro FPGA Device (XC2VP30). The placed and routed IP core has an area utilization of only 13% and clock speed of 50MHz. The GA core can be customized in terms of the population size, number of generations, cross-over and mutation rates, and the random number generator seed. The GA engine can be tailored to a given application by interfacing with the application specific fitness evaluation module as well as the required storage memory (to store the current and new populations). The core is soft in nature i.e., a gate-level netlist is provided which can be readily integrated with the user's system. The GA IP core can be readily used in FPGA based platforms for space and military applications (for e.g., surveillance, target tracking). The main advantages of the IP core are its programmability, small footprint, and low power consumption. Examples of concept systems in sensing and surveillance domains will be presented.

Paper Details

Date Published: 29 April 2009
PDF: 15 pages
Proc. SPIE 7347, Evolutionary and Bio-Inspired Computation: Theory and Applications III, 73470M (29 April 2009); doi: 10.1117/12.820572
Show Author Affiliations
Srinivas Katkoori, Univ. of South Florida (United States)
Pradeep Fernando, Univ. of South Florida (United States)
Hariharan Sankaran, Univ. of South Florida (United States)
Adrian Stoica, Jet Propulsion Lab. (United States)
Didier Keymeulen, Jet Propulsion Lab. (United States)
Ricardo Zebulum, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 7347:
Evolutionary and Bio-Inspired Computation: Theory and Applications III
Teresa H. O'Donnell; Misty Blowers; Kevin L. Priddy, Editor(s)

© SPIE. Terms of Use
Back to Top